Some companies provide web analytics tools and products for website owners to analyze consumer behavior on the Internet. Examples of such products include Google Analytics and web analytics products provided by Omniture. One technique used by some web analytics tools and products is to apply one or more JavaScript™ tags to each webpage within a particular website of interest, or alternatively, in a footer of various webpages within a website of interest. These tags signal a server to monitor consumer attributes while a consumer is visiting the website via an Internet browser or other similar viewing tool, such as what he or she clicks on, which webpages he or she navigates to, etc. The code typically monitors each visitor to the website by placing a cookie on each consumer's computer. Some or all of the monitored consumer behavior can be aggregated by respective IP (Internet Protocol) and URL (uniform resource locator) addresses to provide consumer usage statistics to the website's owner or host for some or all visitors to the website. The website owner may access the statistics and any associated reports through an Internet browser-based interface, e-mail based reports, private client consumer interface, or data feed to monitor activity on his or her website.
Other companies offer industry-based consumer data for usage of the Internet. Examples of such companies include ComScore, Quantcast, Hitwise, Nielson Online, and Compete.com. Typically these companies measure consumer behavior by combining data from one or more Internet service providers (ISPs) with panel-type data, direct site measurement through a JavaScript tag, or data from one or more selected consumers who allow a company to track their behavior by way of an application program, which may be installed on their computer or operating in conjunction with their Internet browser, or by way of routing the data through a proxy. This data is then aggregated to offer consumer trend data at the site level, such as the number of visitors to automotive sites in a given period of time or the search terms consumers used to locate those automotive sites. Multiple sites can be grouped together into an industry category to look at overall traffic patterns to a specific industry; however these companies cannot aggregate and measure product level trend data across multiple sites beyond search term frequency. An example of this would be aggregating all web traffic to web content containing a specific car model for a given period of time, in addition to the search terms used to locate that specific car model (if a consumer used a search engine to find that specific webpage).
Additional companies such as Nielsen BuzzMetrics focus on mining the text on web pages from social networking sites such as MySpace, and other types of blogs, for the purposes of measuring consumer sentiment and the growth rate of content around a specific topic or keyword. These companies utilize different methods of natural language processing to identify topics or keywords within blog content. While this data can be aggregated to determine the ‘growth rate’ or ‘mention rate’ of specific keywords, current methods cannot determine the actual number of consumer visits to the blog web pages and social network web pages where those keywords were found.
Thus, conventional tools focus either on consumer demographics and website traffic statistics (at the site level), such as site rankings, or the growth rate and consumer sentiment around specific keywords, which in some instances may not be useful or particularly relevant measures of consumer interest in or demand for specific content.
Therefore, a need exists for systems and methods for identifying and measuring trends in consumer content demand within vertically associated websites and related content.